COVID-19 data sharing and collaboration

Abstract

There is an immediate need to study COVID-19, and the COVID-19 Data Archive (COVID-ARC) provides access to data along with user-friendly tools for researchers to perform analyses to better understand COVID-19 and encourage collaboration on this research. The COVID-19 pandemic has been spreading rapidly across the world, and there are still many unknowns about COVID-19. There is an urgent need for scientists around the world to work together to model the virus, study how the virus has changed and will change over time, understand how it spreads, and study transmission after vaccination. COVID-ARC can also prepare scientists for future pandemics by putting the infrastructure in place to enable researchers to aggregate data and perform analyses quickly in the event of an emergency. We have developed a platform of networked and centralized web-accessible data archives to store multimodal data related to COVID-19 and make them broadly available and accessible to the world-wide scientific community to expedite research in this area. COVID-ARC provides tools for researchers to visualize and analyze various types of data as well as a website with tools for training, announcements, virtual information sessions, and a knowledgebase wherein researchers post questions and receive answers from the community.

A Novel Threshold-Based Segmentation Method for Quantification of COVID-19 Lung Abnormalities

“…For these reasons, we propose a threshold-based semiautomatic segmentation method to generate ROI segmentations from lung CT available on COVID-19 Data Archive (COVID-ARC) ( https://covid-arc.loni.usc.edu ) which curates and disseminates multimodal and longitudinal datasets related to COVID-19 [ 22 ]. This segmentation method is used to calculate the percentage of lung abnormality (PLA) to determine COVID-19 severity and improve analysis of disease progression in follow-up CT.…”